Researchers uncover brain-network dynamics in schizophrenia
Researchers at Georgia State University have identified a previously unknown aspect of schizophrenia that offers a new way to understand how the disorder affects large-scale brain coordination. In a new study, published in the journal Translational Psychiatry, researchers introduced a method for measuring how brain networks maintain balanced activity and recover when that balance is disrupted.
Scientists at Georgia State University have discovered a new facet of schizophrenia that could transform understanding of the disorder. In a study published in the journal Translational Psychiatry, researchers introduced a technique to measure how brain networks maintain equilibrium and recover from disruption. This method revealed that individuals with schizophrenia experience more frequent imbalances in brain network activity and struggle more with restoring balance after it is lost.
The lead researcher, Sir-Lord Wiafe, expressed excitement about the unexpected finding, stating that it was hidden in plain sight. Prior research on schizophrenia mainly focused on whether brain regions worked in sync, but the Georgia State-led team asked whether different brain networks engaged at proportional strengths. They developed a framework to align the timescales of brain activity, allowing them to compare signal strength more accurately across regions.
People with schizophrenia showed greater imbalance in signal strength (amplitude), returned to unbalanced states more often, and recovered more slowly. However, the slower recovery was not due to increased randomness in brain activity. Instead, the brains of people with schizophrenia have difficulty steering themselves back to balanced signal strength after a disturbance.
The differences in recovery patterns correspond to various aspects of schizophrenia, such as hallucinations, delusions, reduced motivation, and emotional expression. The new framework could help researchers study brain coordination in other psychiatric and neurological disorders, potentially leading to better understanding and treatment options.
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